Center for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Department of Health Promotion and Community Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Vaccine. 2024 Apr 11;42(10):2646-2654. doi: 10.1016/j.vaccine.2024.02.054. Epub 2024 Mar 13.
COVID-19 vaccine acceptance among refugees in the Arab region remains low. This study aimed to examine the prevalence, reasons and predictors of intention to refuse the COVID-19 vaccine among older Syrian refugees in Lebanon.
A nested cross-sectional study within a longitudinal study among older Syrian refugees in Lebanon. The sampling frame was a complete listing of beneficiary households of a humanitarian organization with at least one adult aged 50 years or older. Telephone surveys were completed at months 1 starting September 2020 (wave 1), months 2 (wave 2), months 5 (wave 3), months 6 (wave 4) and months 17 (wave 5) in March 2022. Logistic regression models were used to identify predictors of intention to refuse the COVID-19 vaccine. Models were internally validated using bootstrap methods and the models' calibration and discrimination were presented.
Of 3167 Syrian refugees, 61.3% intended to receive the COVID-19 vaccine, 31.3% refused, and 7.4% were undecided. Reasons for vaccine refusal were: preference to follow preventive measures (27.4%) and belief that the vaccine is not essential (20.7%). Furthermore, 57.1% of participants registered to take the COVID-19 vaccine in wave 5. Irrespective of vaccination intention, reasons for not registering included: not wanting to receive the vaccine, and being unsure whether to take it. Predictors of intention to refuse the COVID-19 vaccine included: being a female, older age, having elementary education or above, living outside informal tented settlements, perceiving COVID-19 as not severe and vaccines as not safe or effective, and using social media for information on COVID-19. After adjusting for optimization, the final model showed moderate discrimination (C-statistic: 0.651 (95% CI:0.630-0.672)) and good calibration (C-slope: 0.93 (95% CI: 0.823-1.065)).
This study developed a predictive model for vaccination intention with a moderate discriminative ability and good calibration. Prediction models in humanitarian settings can help identify refugees at higher risk of not intending to receive the COVID-19 vaccine for public health targeting.
在阿拉伯地区，COVID-19 疫苗在难民中的接受率仍然很低。本研究旨在调查黎巴嫩老年叙利亚难民拒绝 COVID-19 疫苗的意愿的流行率、原因和预测因素。
在黎巴嫩老年叙利亚难民的纵向研究中嵌套横断面研究。抽样框架是一个人道主义组织受益家庭的完整清单，其中至少有一名 50 岁或以上的成年人。电话调查于 2020 年 9 月开始的第 1 个月（第 1 波）、第 2 个月（第 2 波）、第 5 个月（第 3 波）、第 6 个月（第 4 波）和 2022 年 3 月的第 17 个月（第 5 波）进行。使用逻辑回归模型来确定拒绝 COVID-19 疫苗的意愿的预测因素。使用自举方法对内部分数进行了内部验证，并展示了模型的校准和区分能力。
在 3167 名叙利亚难民中，61.3%表示打算接种 COVID-19 疫苗，31.3%表示拒绝，7.4%表示犹豫不决。拒绝疫苗的原因是：更喜欢采取预防措施（27.4%）和认为疫苗不是必需的（20.7%）。此外，57.1%的参与者在第 5 波中注册接种 COVID-19 疫苗。无论接种疫苗的意愿如何，不注册的原因包括：不想接种疫苗，以及不确定是否接种疫苗。拒绝 COVID-19 疫苗的意愿的预测因素包括：女性、年龄较大、接受过小学或以上教育、居住在非正式帐篷定居点外、认为 COVID-19 不严重以及疫苗不安全或有效，以及使用社交媒体获取有关 COVID-19 的信息。在调整优化后，最终模型显示出中等的区分能力（C 统计量：0.651（95%CI：0.630-0.672））和良好的校准（C 斜率：0.93（95%CI：0.823-1.065））。
本研究开发了一种具有中等区分能力和良好校准的疫苗接种意愿预测模型。在人道主义环境中，预测模型可以帮助识别出不太愿意接种 COVID-19 疫苗的难民，以便针对公共卫生目标进行干预。
